When managing database systems, it is often necessary to transfer data between heterogeneous systems. To facilitate such a process, various tools have been developed to extract, transform, and load (ETL) data from a source database to a target database. These tools, however, are often specialized and configured for particular proprietary database systems. Accordingly, developers often require specific knowledge of the proprietary systems, which limits the ability to update and scale such systems. Moreover, such ETL tools often require particular hardware requirements with minimal configurability. Accordingly, currently available ETL tools are not well-suited for current development architectures that require customization and scalability. Accordingly, there is a need for a framework that provides ETL tools that are flexible and deployable across various types of infrastructures.